Mingda Li

5k citations
125 papers · 3.5k · h-index 32

Impact in

Papers in

    • Machine Learning in Materials Science 23
    • Thermal properties of materials 10
    • 2D Materials and Applications 8
    • Microstructure and mechanical properties 7
    • Advanced Thermoelectric Materials and Devices 6
    • Topological Materials and Phenomena 31
    • Magnetic properties of thin films 6

Mingda Li

117 papers receiving 3.4k citations

Peers

Mingda Li
Comparison fields: 5 of 80
  • Materials Chemistry 1.7k
  • Atomic and Molecular Physics, and Optics 866
  • Condensed Matter Physics 268
  • Electronic, Optical and Magnetic Materials 279
  • Structural Biology 35
Replace Jean‐François Guillemoles with:
Jean‐François Guillemoles France
Andrew G. Norman United States
Wojciech Paszkowicz Poland
Akira Sakai Japan
Masao Yonemura Japan
John C. C. Fan United States
Gregor Hlawacek Germany
B. Rech Germany
Christopher L. Hinkle United States
S.J.C. Irvine United Kingdom
Mingda Li relative to Jean‐François Guillemoles France Jean‐François Guillemoles's profile →
Citations per field
00.5×2×3.4×
Jean‐François Guillemoles · 1×
Citations per year

Countries citing papers authored by Mingda Li

Since Specialization
Citations

This map shows the geographic impact of Mingda Li's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Mingda Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mingda Li more than expected).

Fields of papers citing papers by Mingda Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mingda Li. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Mingda Li. The network helps show where Mingda Li may publish in the future.

Co-authors

The 25 scholars most cited alongside Mingda Li, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Mingda Li Line = papers co-authored together Mingda Li links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 125 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2019318
2 2018154
3 2020133
4 2016116
5 2015110
6 2017106
7 202296
8 201689
9 202189
10 201886
11 201886
12 201582
13 201580
14 202076
15 201870
16 202367
17 202265
18 201763
19 202063
20 202461

About Mingda Li

Mingda Li is a scholar working on Materials Chemistry, Atomic and Molecular Physics, and Optics, Condensed Matter Physics, Electronic, Optical and Magnetic Materials and Radiation, having authored 125 papers that have together received 3.5k indexed citations. Recurring topics across this work include Topological Materials and Phenomena (31 papers), Machine Learning in Materials Science (23 papers), Physics of Superconductivity and Magnetism (10 papers), Thermal properties of materials (10 papers), 2D Materials and Applications (8 papers), Microstructure and mechanical properties (7 papers), Advanced Thermoelectric Materials and Devices (6 papers) and Magnetic properties of thin films (6 papers). The work is most often cited by research in Materials Chemistry (1.7k citations), Atomic and Molecular Physics, and Optics (866 citations), Condensed Matter Physics (268 citations), Electronic, Optical and Magnetic Materials (279 citations) and Structural Biology (35 citations). Mingda Li has collaborated with scholars based in United States, China and Japan. Frequent co-authors include Gang Chen, Jiawei Zhou, Cui‐Zu Chang, Yimei Zhu, Zhiwei Ding, Thanh Nguyen, Bai Song, Fei Han, Lijun Wu and Ju Li. Their work appears in journals such as Nature Communications, Physical review. B., Science Advances, Physical Review Letters and Advanced Materials.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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